As those of you who know rail history understand, with Stephenson as your last name, you’re bound to have a strong interest in railroads!Add in the fact that I was associate producer of an award-winning documentary on the subject back in the early 70’s, and it’s no wonder I was hooked when I got a chance to meet with some of Siemens’s top rail executives on my trip to Barcelona last week (Disclaimer: Siemens paid my expenses, but didn’t dictate what I covered, nor did they have editorial review of this piece).

What really excites me about railroads and the IoT is that they neatly encapsulate the dramatic transformation from the traditional industrial economy to the IoT: on one hand, the railroad was perhaps THE most critical invention making possible 19th century industry, and yet it still exists, in recognizable but radically-evolved form, in 2016. As you’ll see below, trains have essentially become laboratories on wheels!

I dwelt on the example of the Union Pacific in my e-book introduction to the IoT, SmartStuff, because to CIO Lynden Tennison was an early adopter, with his efforts focused largely on reducing the number of costly and dangerous derailments, through measures such as putting infrared sensors every twenty miles along the rail bed to spot “hotboxes,” overheating bearings. That allowed an early version of what we now know as predictive maintenance, pulling cars off at the next convenient yard so the bearings could be replaced before a serious problem. Even though the technology even five years ago was primitive compared to today, the UP cut bearing-related derailments by 75%.

Fast-forward to 2016, and Siemens’s application of the IoT to trains through its Mobility Services is yielding amazing benefits: increasing reliability, cutting costs, and even leading to possible new business models. They’ve taken over maintenance for more than 50 rail and transit programs.

While I love IoT startups with a radical new vision and no history to encumber them, Siemens is a beacon to those companies firmly rooted in manufacturing which may wonder whether to incorporate the IoT in their services and strategy. I suspect that its software products are inherently more valuable than competitors from pure-play software firms at commercial launch because the company eats its own dogfood and applies the new technology first to the products it manufactures and maintains — closing the loop.

Several of its executives emphasized that one of the advantages Siemens feels they enjoy is that their software engineers in Munich work in a corner of an old locomotive factory that Siemens still operates, so they can interact with those actually building and maintaining the engines on a daily basis. When it comes to security issues, their experience as a manufacturer means they understand the role of each component of the signaling system. Dr. Sebastian Schoning, ceo of Siemens client Gehring Technologies, which manufactures precision honing tools, told me that it was easier to sell these digital services to its own client base because so much of their current products include Siemens devices, giving them confidence in the new offerings. GE enjoys the same advantages of combining manufacturing and digital services with its Evolution Series locomotives.

The key to Siemens’s Mobility Services is Sinalytics, its platform architecture for data analysis not just for rail, but also for industries ranging from medical equipment to wind farms. More than 300,000 devices currently feed real-time data to the platform, Consistent with my IoT-centric “Circular Company” vision, Sinalytics capitalizes on the data for multiple uses, including connectivity, data integration, analytics, and the all-important cyber security — they call the result not Big Data, but Smart Data. As with data services from jet turbine manufacturers such as Rolls Royce and GE, the platform also allows merging the data with data from sources such as weather forecasts which, in combination, can let clients optimize operating efficiency on a real-time M2M basis.

With the new approach, trains become IoT laboratories on wheels, combining all of the key elements of an IoT system:

Sensing: there are sensors on the engines and gearboxes, plus vibration sensors onmicrophones measure noises from bearings in commuter trains. They can even measure how engine oil is aging, so it can be changed when really needed, rather than on an arbitrary schedule.

Algorithms to make sense of the data and act on it. They read out patterns, record deviations & compare them with train control systems or vehicles of the same type.

Predictive maintenance replaces scheduled maintenance, dramatically reducing down-time and catastrophic failure.For example: “There’s a warning in one of the windows (of the control center display): engine temperature unusual. ‘We need to analyze the situation in greater depth to know what to do next— we call it‘root cause analysis,” (say) Vice-President for Customer Support Herbert Padinger. ‘We look at its history and draw on comparative data from the fleet as a whole.’ Clicking on the message opens a chart showing changes in temperature during the past three months. The increased heat is gradually traced to a signal assembly. The Siemens experts talk with the customer to establish how urgent the need for action is, and then takes the most appropriate steps.” He says that temperature and vibration analyses from the critical gearboxes gives Siemens at least three days advance notice of a breakdown — plenty of time for maintenance or replacement. Predictive maintenance is now the norm for 70-80% of Siemens’s repairs.

Security (especially important given all of the miles of track and large crowds on station platforms): it includes video-based train-dispatch and platform surveillance using its SITRAIL D system, as well as cameras in the trains. The protections have to run the gamut from physical attacks to cyber attacks. For security, the data is shared by digital radio, not networks also shared by consumers.

When operations are digitized, it allows seamlessly integrating emerging digital technologies into the services. Siemens Digital Services also included augmented reality (so repair personnel can see manuals on heads-up displays), social collaboration platforms, and — perhaps most important — 3-D printing-based additive manufacturing, so that replacement parts can be delivered with unprecedented speed. 3-D printing also allows dramatic reduction in parts inventories and allows replacement of obsolete parts that may no longer be available through conventional parts depots or even — get this — to improve on the original part’s function and/or durability, based on practical experience gained from observing the parts in use.Siemens has used 3-D printing for the past last 3 years, and it lets them assure that they will have replacements for the locomotive’s entire lifespan, which can exceed 30 years.

The results of the new approach are dramatic.

None of the Velaro trains that Siemens maintains for several operators have broken down since Sinalytics was implemented. Among those in Spain only 1 has left more than 15 min. behind time in 2,300 trips: .0004%!

Reliability for London’s West Coast Mainline is 99.7%

Perhaps most impressive, because of the extreme cold conditions it must endure, the reliability rate for the Velaro service in Russia is 99.9%!

Their ultimate goal is a little higher: what Siemens calls (pardon the pun) 100% Railability (TM).

And, consistent with what other companies find when they fully implement not only IoT technology, but also what I like to call “IoT Thinking,” when it does reach those previously inconceivable quality benchmarks, the company predicts that, as the software and sensors evolve, the next stage will be new business models in which billing will be determined by guaranteeing customers availability and performance.

PS: I’ll be posting more about my interviews with Siemens officials and the Gartner event in coming days.

he downplays AR in industrial setting: walking in industrial setting with lithium battery strapped to your head is dangerous.

big benefit: less capital expense when they build next mine. For example, building the town for the operators — so eliminate the town!

take existing processes & small improvements, but IoT-centric biz, eliminating people, might eliminate people. Such as a human-less warehouse. No more pumping huge amount of air underground. Huge reduction with new system. Mine of future: smaller holes. Possibility of under-sea mining.

mining has only had incremental change.

BHP mining’s railroad — Western Australia. No one else is involved. “Massive experiment.”

Sound sensing can be important in industrial maintenance. All sorts of real-time info.

Afternoon panel on “IoT of Moving Things” starts with all sorts of incredible factoids (“since Aug., Singapore residents have had access to self=driving taxis”/ “By 2030, owning a car will be an expensive self-indulgence and will no longer be legal.”

vehicles now have broader range of connectivity now

do we really want others to know where we are? — privacy again!

who owns the data?

what challenges do we need to overcome to turn data into information & valuable insight that will help network and city operators maximize efficiency & drive improvement across our transportation network?

think of evolution: now car will be software driven, then will become living room or office.

data is still just data, needs context & location gives context.

cities have to re-engineer streets to become intelligent streets.

must create trust among those who aren’t IT saavy.

do we need to invest in physical infrastructure, or will it all be digital?

case study: one car company w/ engine failures in 1 of 3 cars gave the consultants data to decide on what was the problem.

start with high-scale traditional IT structures, but with new emphasis on cloud, etc. IT system now partially inside your org. and part outside. We are half-way through transition to cloud: half of sales support now through cloud. More financial, HR & other functions. General trend toward cloud, but still some internal processes as necessary. Must clean up traditional inside processes.

“Ecosystems are the next evolution of Digital”

Must learn to measure your investments in customer experience.

Starting to explore VR & AR (personal shout out to PTC & clients such as Caterpillar!!)

must understand customer’s intent through advanced algorithms. Create solutions to problems they don’t even know they have!

next domain of new platform: Things:

build strategies with two lenses: consumer preferences, AND the enterprise IoT lens.

leverage exponential growth in connected things

27445 exabytes of data by 2020!

can’t just bolt on new systems on old ones: must rework existing systems to include devices — processes, workflow, much harder (i.e., my circular company paradigm).

intelligence: how your systems learn and decide independently

algorithms– algorithmic intelligence — drives decisions

now, AI, driven by machine learning. Machines learn from experience.

information is new code base

we will employ people to train things to learn from experience through neural networks

Could the IoT’s most profound impact be on management and corporate organization, not just cool devices?

I’ve written before about my still-being-refined vision of the IoT — because it (for the first time!) allows everyone who needs instant access to real-time data to do their jobs and make better decisions to share that data instantly — as the impetus for a management revolution.

“For companies grappling with the transition (to the IoT), organizational issues are now center stage — and there is no playbook. We are just beginning the process of rewriting the organization chart that has been in place for decades.”

If I’m right, the IoT could let us switch from the linear and hierarchical forms that made sense in an era of serious limits to intelligence about things and how they were working at thaFor companies grappling with the transition, organizational issues are now center stage—and there is no playbook. We are just beginning the process of rewriting the organization chart that has been in place for decades.t moment, to circular forms that instead eliminate information “silos” and instead give are circular, with IoT data as the hub.

This article expands on that vision. I’ve tried mightily to get management journals to publish it. Several of the most prestigious have given it a serious look but ultimately passed on it. That may be because it’s crazy, but I believe it is feasible today, and can lead to higher profits, lower operating costs, empowering our entire workforces, and, oh yeah, saving the planet.

Audacious, but, IMHO, valid. Please feel free to share this, to comment on it, and, if you think it has merit, build on it.

Thanks,

W. David Stephenson

The IoT Allows a Radical, Profitable Transformation to Circular Company Structure

by

W. David Stephenson

Precision assembly linesand thermostats you can adjust while away from home are obvious benefits of the Internet of Things (IoT), but it might also trigger a far more sweeping change: swapping outmoded hierarchical and linear organizational forms for new circular ones.

New org charts will be dramatically different because of an important aspect of the IoT overlooked in the understandable fascination with cool devices. The IoT’s most transformational aspect is that, for the first time,

everyone who needs real-time data to do their jobs better or
make better decisions can instantly share it.

That changes everything.

Linear and hierarchical organizational structures were coping mechanisms for the severe limits gathering and sharing data in the past. It made sense then for management, on a top-down basis, to determine which departments got which data, and when.

The Internet of Things changes all of that because of huge volumes of real-time data), plus modern communications tools so all who need the data can share it instantly.

This will allow a radical change in corporate structure and functions from hierarchy: make it cyclical, with real-time IoT data as the hub around which the organization revolves and makes decisions.

Perhaps the closest existing model is W.L. Gore & Associates. The company has always been organized on a “lattice” model, with “no traditional organizational charts, no chains of command, nor predetermined channels of communication.”Instead, they use cross-disciplinary teams including all functions, communicating directly with each other. Teams self-0rganize and most leaders emerge spontaneously.

As Deloitte’s Cathy Benko and Molly Anderson wrote, “Continuing to invest in the future using yesteryear’s industrial blueprint is futile. The lattice redefines workplace suppositions, providing a framework for organizing and advancing a company’s existing incremental efforts into a comprehensive, strategic response to the changing world of work.”Add in the circular form’s real-time data hub, and the benefits are even greater, because everyone on these self-organizing teams works from the same data, at the same time.

You can begin to build such a cyclical company with several incremental IoT-based steps.

“G.E. is adopting practices like releasing stripped-down products quickly, monitoring usage and rapidly changing designs depending on how things are used by customers. ‘We’re getting these offerings done in three, six, nine months,’ (Vice-President of Global Software William Ruh said). ‘It used to take three years.’”

New IoT and data-analytics tools are coming on the market that could facilitate such a shift. GE’s new tool, “Digital Twins,” creates a wire-frame replica of a product in the field (or, for that matter, a human body!) back at the company. Coupled with real-time data on its status, it lets everyone who might need to analyze a product’s real-time status (product designers, maintenance staff, and marketers, for example) to do so simultaneously.

The second step toward a cyclical organization is breaking down information silos.

Since almost every department has some role in creation and sales of every product, doesn’t it make sense to bring them together around a common set of data, to explore how that data could trigger coordinated actions by several departments?

Collaborative big-data analysis tools such as GE’s Predix, SAP’s HANA, and Tableau facilitate the kind of joint scrutiny and “what-if” discussions of real-time data that can make circular teamwork based on IoT-data sharing really achieve its full potential.

The benefits are even greater when you choose to really think in circular terms, sharing instant access to that real-time data not only companywide, but also with external partners, such as your supply chain and distribution network – and even customers – not just giving them some access later on a linear basis.For example, SAP has created an IoT-enabled vending machine. If a customer opts in, s/he is greeted by name, and may be offered “your regular combination” based on past purchases, and/or a real-time discount. That alone would be neat from a marketing standpoint, but SAP also opened the resulting data to others, resulting in important logistics improvements. Real-time machine-to-machine (M2M) data about sales at the new vending machines automatically reroute resupply trucks to those machines currently experiencing the highest sales.

With the IoT, sharing data can make your own product or service more valuable. With the Apple HomeKit, you can say “Siri, it’s time for bed,” and the Hue lights dim, Schlage lock closes, and Ecobee thermostat turns down. By sharing real-time IoT data, each of these companies’ devices become more valuable in combinations than they are by themselves.

Hierarchical and linear management is outmoded in the era of real-time data from smart devices. It is time to begin to replace it with a dynamic, circular model with IoT data as its hub.

Simultaneously sharing real-time data and collaborating (vs. linear methods where departments work in isolation from each other and sequentially) is a major theme of my “Circular Company” vision.

At the PTC ThingWorx expo in June one of the themes was “concurrent engineering“), which could be a major tool in making the circular company a reality. The company’s Creo Advanced Assembly Extension lets the the lead designer plan the assembly’s “skeleton” to give all the subassembly teams a common work basis and to include critical design info in the subassemblies. This lets each team work in parallel. If the lead engineer modifies the primary design, all the subassemblies will modify automatically. The process transfers seamlessly to the assembly line.

According to Wikipedia, the concept also fits nicely with the “circular economy” concept that’s gaining strength, by considering factors such as end-of-life disposal and recycling, which is a great bonus of the “circular company”:

“.. part of the design process is to ensure that the entire product’s life cycle is taken into consideration. This includes establishing user requirements, propagating early conceptual designs, running computational models, creating physical prototypes and eventually manufacturing the product. Included in the process is taking into full account funding, work force capability and time. A study in 2006 claimed that a correct implementation of the concurrent design process can save a significant amount of money, and that organizations have been moving to concurrent design for this reason.[3] It is also highly compatible with systems thinking [which, BTW, is what originally introduced me to this concept, many years ago, through the writings of Peter Senge and Jay Forrester, who, BTW, is still kickin’ at 97!] and green engineering.”

Come on, gang: hierarchy and linear processes are soooo 20th century. Get with the program.

Two major developments in the 3-D printing world, from Fictiv and (who woulda thunk it!) UPS, make me think the time has come for “distributing manufacturing” and getting away from the old massive, manufacturing mentality exemplified by Ford’s River Rouge plant.

OK, first a confession and a little history. Being short & named David, I’ve always had a fascination with David & Goliath, and you can bet who I’d root for. I also was deeply touched by two visionaries in my past:

Steve Clay-Young, who used to run the workshop at the old Boston Architectural Center & turned me on to a neat, nearly-forgotten bit of WWII history: either Popular Science or Popular Mechanix (can’t remember which), organized a network of hobbyists with metal lathes, who played a major role in the war effort. The magazine published plans for turning metal for munitions, and these guys each worked in their workshops to make them.

Eric Drexler, the nano-tech guru, spoke at the Eco-Tech conference in the ’90s about his vision of a bread-box-size gizmo on your kitchen counter that would churn out all sorts of customized products for you.

Now, it’s all taking place, and I suspect 3D printing will be a crucial element in the IoT-based transformation of the economy.

Fictiv distributed manufacturing model

Fictiv is a startup founded to “democratize manufacturing,” which just went public with its new “distributed manufacturing” service using a nationwide network of 3D high quality printers and CNC machines:

“We route parts to machine with open capacity so you don’t wait 5 days for a part that takes 5 hours…. We aggregate orders so every customer receives the benefits of large purchasing power….”

Perhaps coolest, “Parts are produced as close to customers as possible to reduce inefficiencies in logistics and shipping lead-time” so that (for an extra charge) they’re fabricated and delivered in 24 hours, and otherwise delivered in two days. I suspect that, just as having sensors on their products that results in real-time feedback allowing GE to compress the design cycle, especially upgrades, that this proximity and quick turn-around will allow designers to radically alter the design process by “failing rapidly,” just the way early spread-sheet software allowed business managers to do “what-if” hypotheticals for the first time.

By bundling orders, they give startups the bargaining power of large companies.As co-founder Dave Evans, an experienced product design pro, says, distributed, local manufacturing can even the playing field for smaller companies, especially startups just designing their first products:

“When ordering from a large manufacturing company, parts need to navigate through their complex system and then be shipped from the machine warehouse direct to the customer, increasing lead times.

From an engineer’s perspective, when you’re in the prototyping and ideation stages, time is everything and even a 1-2 day loss from a 3PL (third-party logistics player) matters significantly.

What’s important to consider here is that in manufacturing, things can and will go wrong. So when remote manufacturers inevitably have to manage errors, there’s a lot of complexity to deal with …. This is very evident in overseas mass manufacturing, which is why companies put engineers as close to the source as possible. It’s amazing how few companies consider the same principles during the early prototyping stages of a product when time is everything.

The beauty in working with smaller, local manufacturers on the other hand, is that parts can be picked up as soon as they’re ready or delivered via same-day courier, saving you the 1-2 days of shipping. In addition, if things go wrong (they always do), smaller shops have more agility, fewer organizational layers, and in general can respond more quickly compared with their larger counterparts.”

3D printing at The UPS Store

Equally important is the continuing stream of 3D services being offered by UPS. which recently announced a nationwide on-demand 3D printing network. The network will combine 3D printers at more than 60 The UPS Stores® and Fast Radius’ On Demand Production Platform™ and 3D printing factory in Louisville, KY. My friends at SAP will marry its SAP’s extended supply chain solutions will be integrated with the UPS 3D network and — most important — its global logistics network “to simplify the industrial manufacturing process from digitization, certification, order-to-manufacturing and delivery.”

If I’m correct, the UPS network will concentrate on prototyping at this point, but it’s easy to see that it could soon have a dramatic impact on the replacement parts industry. Why should the manufacturer warehouse a large supply of spare parts, just because they might be needed, when they could instead simply transmit the part’s digital file to the nearest UPS 3D printer, generate the part, and use UPS to deliver it in a fraction of the time.

Combine that with the predictive maintenance possible with feedback from sensors on products, and you truly have a revolution in product design and maintenance as well as manufacturing. It would also foster the IoT-based circular company vision that I’ve been pushing, because supply chain, manufacturing, distribution, and maintenance would all be linked in a great circle.